文章基本信息

标题：Model Criticism in Latent Space
本地全文：下载
作者：Sohan Seth ; Iain Murray ; Christopher K. I. Williams 等
期刊名称：Bayesian Analysis
印刷版ISSN：1931-6690
电子版ISSN：1936-0975
出版年度：2019
卷号：14
期号：3
页码：703-725
DOI：10.1214/18-BA1124
语种：English
出版社：International Society for Bayesian Analysis
摘要：Model criticism is usually carried out by assessing if replicated data generated under the fitted model looks similar to the observed data, see e.g. Gelman, Carlin, Stern, and Rubin (2004, p. 165). This paper presents a method for latent variable models by pulling back the data into the space of latent variables, and carrying out model criticism in that space. Making use of a model’s structure enables a more direct assessment of the assumptions made in the prior and likelihood. We demonstrate the method with examples of model criticism in latent space applied to factor analysis, linear dynamical systems and Gaussian processes.
关键词：model criticism; latent variable models; factor analysis; linear dynamical systems; Gaussian processes.